For the first time ever, the software sector is trading at a discount to the S&P 500 on a free cash flow multiple basis. The median software business trades at 18-19x free cash flow, compared to the S&P 500's 28x, signaling a historically cheap valuation for the sector.
For the first time, the high-multiple software industry faces a potential existential threat from AI. Even the possibility of disruption is enough to compress valuations, causing massive dispersion where indices look calm but underlying sectors are experiencing extreme rotation.
The recent software stock drawdown is not about poor current performance; many companies are still beating earnings. Instead, the market is pricing in a massive "terminal value risk" from AI, valuing companies as if they will decline in perpetuity, creating a historic disconnect between current fundamentals and long-term valuation.
The VC market is obsessed with AI companies showing "zero to 100 in a year" growth. This creates a blind spot for high-quality, traditional software companies. A business growing 5x annually is a fantastic investment by any historical standard but now struggles for attention.
The downturn in software stocks isn't tied to current earnings. Instead, investors are repricing the entire sector, removing the premium they once paid for its perceived safety and stable, long-term contracts, which are now threatened by AI disruption.
Sridhar Ramaswamy suggests software valuation multiples are contracting because investors see through the strategy of just adding an 'AI SKU.' The market believes this approach won't win, favoring integrated, consumption-based models where customers only pay for demonstrated value from AI.
As AI commoditizes software creation and data migration, the high-margin, sticky nature of SaaS will disappear. Klarna's CEO predicts that valuations will compress from historical 20-30x price-to-sales multiples down to 1-2x, similar to how low-moat utility companies are valued.
Software has long commanded premium valuations due to near-zero marginal distribution costs. AI breaks this model. The significant, variable cost of inference means expenses scale with usage, fundamentally altering software's economic profile and forcing valuations down toward those of traditional industries.
Investor uncertainty about the long-term viability of software business models due to AI is causing a fundamental shift in valuation. Instead of paying a premium for future growth, investors are now demanding immediate returns like dividends, effectively treating established software firms as value stocks rather than growth stocks.
The market has overreacted to AI's threat to SaaS giants like Salesforce and Adobe. While AI can replicate code, it cannot easily replace the years of deep integration into client billing, customer service, and employee training. These high switching costs are being ignored, making their stocks undervalued.
The market has fundamentally reset how it values mature SaaS companies. No longer priced on revenue growth, they are now treated like industrial firms. The valuation bottom is only found when they trade at free cash flow multiples that fully account for stock-based compensation.